Rob Allen

The true measure of a software developer is being able to deliver value in the simplest possible way. It isn't knowing the latest languages, frameworks, or techniques; it's knowing when not to use them. It isn't delivering lots of sparkly new features; it's delivering the one feature that gives its users leverage they need. It isn't sitting behind a screen 16 hours a day; it's knowing who to talk to and building relationships. It isn't being right; it's being an inspiration.

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'We only hire senior developers' Congrats! You're building a time bomb. Here's why: Senior-only teams create: • Echo chambers of outdated practices • Zero knowledge transfer • Expensive solutions to simple problems • 10 architects, no builders What you're really missing: • Fresh perspectives • Hunger to learn • Questions that challenge assumptions • Future leaders The brutal truth: • Your 'senior' requirements are fear-based • Your '10 years experience' is arbitrary • Your 'no junior devs' policy is expensive technical debt Why this matters: • Innovation needs new eyes • Growth requires teaching • Sustainability demands succession • AI is leveling the experience gap anyway How to fix it: 1. Hire for potential, not just experience 2. Create mentorship structures 3. Balance your team pyramid 4. Accept that juniors today code better than seniors did 5 years ago Remember: Today's 'risky' junior is tomorrow's 'savior'. What's your take on the senior-only trend? Drop your thoughts below 👇 *** P.S. If your entire team is senior developers, who's asking the 'stupid' questions that prevent stupid mistakes?

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Tonight I will be joining a session with the Chrome DevTools team to talk about the network debugging experience in DevTools. Thanks Barry Pollard for connecting me 🙌 One of my own feedback points: 👉 It’s difficult to capture and share request + response details. When a network error happens, developers often need both the request info (URL, headers, params) and the response (body, status code) in one place. Right now, DevTools doesn’t have an easy one-click export or screenshot for this, which would be super useful for bug reports and troubleshooting. --- The team is also focusing on challenges developers face when debugging network issues end-to-end (from back-end to front-end), such as: - Working with / integrating between multiple disjointed systems - State management challenges that make it hard to reproduce bugs reliably - Difficulty understanding the payload of large requests, or dealing with 100s of network requests on a single page (noise, latency, etc.) - The complexity and limitations of end-to-end tracing across deeper back-end components or distributed systems - Difficulty reproducing real-world conditions (e.g. prod vs. dev, latency and bandwidth inconsistencies) - Not being able to inspect network activity due to security constraints 💬 If you’ve got your own pain points with the Network tab, please drop them in the comments and I’ll pass them along! Thanks for your input, everyone 💛

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A common mistake I see: People treat message queues and streams as if they’re interchangeable. They’re not. Here’s the difference 👇 Message Queue (MQ) - Designed for delivery guarantees (at-least-once, exactly-once). - Great for sporadic workloads and asynchronous tasks. - Messages are consumed and removed. Once acknowledged, they’re gone. - Think: order processing, background jobs, retry logic. Stream - Designed for real-time, high-throughput, continuous data. - Data is append-only and replayable. - Multiple consumers can read the same stream independently. - Think: real-time analytics dashboards, fraud detection, monitoring pipelines. Why Streams fit Aaron’s case (real-time analytics for e-commerce): - Freshness matters → Streams process events as they arrive, with low latency. - Replayability matters → If a consumer goes down, it can re-read from the offset. - Scale matters → Streams partition data for massive parallel consumption. A message queue here would introduce unnecessary latency and discard historical events that analytics needs to stay accurate. Rule of thumb: - If you care about delivery → Message Queue. - If you care about freshness & scale → Stream. That’s why the right answer here is: Streams for real-time analytics.

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𝘞𝘩𝘺 𝘠𝘖𝘜𝘙 Automation 𝘧𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬 𝘸𝘪𝘭𝘭 𝘍𝘈𝘐𝘓 𝘪𝘯 6 𝘮𝘰𝘯𝘵𝘩𝘴 (𝘢𝘯𝘥 𝘩𝘰𝘸 𝘵𝘰 𝘧𝘪𝘹 𝘪𝘵) I just audited a $50M company's automation framework. Result? 73% of their tests were failing randomly. Their CTO asked me one question: "How did we go from 10 passing tests to complete chaos?" The Brutal Truth: 85% of Selenium Projects Die the Same Death Month 1: "Our automation is amazing!" Month 6: "Why does everything break when we deploy?" Here's what kills every framework (and the fix): 1️⃣ The "Everything in One Folder" Disaster ❌ Death pattern: UI, API, utils all mixed together ✅ Fix: Dedicated packages → UI, API, POJO, services separated Reality check: Good teams onboard new devs in 2 hours, not 2 weeks. 2️⃣ The "Hardcoded Hell" Problem ❌ Death pattern: URLs, data, timeouts scattered everywhere ✅ Fix: Environment property files + externalized test data Game changer: Switch DEV→QA→PROD with one command. 3️⃣ The "No POJO = No Scale" Trap ❌ Death pattern: Raw JSON strings, manual API payloads ✅ Fix: Request/Response POJOs + schema validation Impact: API tests become 10x more maintainable. 4️⃣ The "Debug Nightmare" Issue ❌ Death pattern: "Test failed" with zero context ✅ Fix: Extent Reports + screenshots + API logs Truth: Debug time drops from 2 hours → 5 minutes The Framework That Actually Scales I've built a production-ready structure that includes: 🏗️ Proper separation of UI/API/POJO layers 🔧 External configurations for all environments 📊 Rich reporting with screenshots & metrics 🚀 CI/CD ready with Docker & Jenkins support 🎯 BDD structure that business teams understand The Bottom Line: Stop building "quick automation scripts." Start building software systems that scale. Your framework should work at test #10 AND test #1000. Want the complete folder structure? 👇 Comment "𝑭𝑹𝑨𝑴𝑬𝑾𝑶𝑹𝑲" and I'll send it to your inbox! Found this helpful? Share with someone struggling with flaky tests! 🚀 -x-x- Full Stack QA & Automation Framework Course with Clearing SDET Coding Rounds: https://lnkd.in/g7tn6Uif #japneetsachdeva

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Flaky tests feel random. They’re not. The patterns are clear: * Timing issues (async workflows, race conditions) * Shared state (bad test isolation, order dependencies) * Environment drift (things that work locally but fail in CI) By definition, though, they’re not obvious to spot. A missing await, an unseeded random number, a fragile assertion. These problems tend to show up after the developer who wrote them has moved on to the next thing, reducing the likelihood that anyone will take time to fix them. AI is going to multiply these issues. It’s *also* going to help us catch them faster. The challenge for leaders: don’t accept flaky tests as inevitable. They’re just tech debt we’ve been too slow to pay down.

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"I’ve been writing tests first since before it had a name, and have trained and coached thousands of other developers in these disciplines. If there’s one thing I’ve learned from all that TDD experience, it’s this: if you don’t want to learn TDD, you won’t." This course book will be 10 years old next year, and due for retirement to coincide with the launch of... well, something new. It's in Goodread's top 5 TDD books, despite never having been for general sale. (If you bought a signed copy, thank you.) I don't track stats, so I don't know how many downloads it's had. But I did order every printed copy, so I know there are about 2,000 sitting on shelves somewhere. I ran an onsite course last year for a regular client, and was gratified to see a bunch of them in their library. Some clients, like Redgate, ordered a box of them. But when you read it, you'll see that it needs updating. The principles are timeless, but the implementations move on. Same chords, different arrangements. In the meantime, get 'em while you can :-) https://lnkd.in/eVm7ghCc

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